text model · Granite · iOS
Can I run Granite 4.1 8B on iPad Pro M4 (16GB, 1TB/2TB config)?
Yes. Granite 4.1 8B runs on iPad Pro M4 (16GB, 1TB/2TB config) at Q4_K_M (~6.8 GB of ~12 GB usable).
Runs at Q4_K_M using ~6.8 GB of ~12 GB usable. You have room for Q8_0 for higher quality.
That figure is at a 4k context and moves about ±15% as context length changes. iPad Pro M4 (16GB, 1TB/2TB config) leaves ~5.2 GB of headroom, room to step up to Q8_0 for higher quality.
- Q4_K_M needed
- ~6.8 GB
- Usable on device
- ~12 GB
- Device memory
- 16 GB
- Best quant
- Q4_K_M
Which quant fits
Running cost · estimate
- Power draw
- ~14 W
- Electricity / 1M tokens
- ~$0.05
- Pays for itself after
- ~3,553M tok
At ~$0.15/kWh and the estimated ~11 tok/s, a million generated tokens costs about $0.05 in electricity. Versus a hosted API at ~$0.5 per million tokens, the ~$1,599 iPad Pro M4 (16GB, 1TB/2TB config) pays for itself after roughly 3,553 million tokens, so local hardware is mostly a fixed cost, not a per-token one. TDP is the peak draw, so this is an upper bound. Assumptions.
How to run it
On iOS use Apple Foundation Models (Built into iOS 26, ~3B on-device model, zero download, fully private.).
- Parameters
- 8.8B
- Q4_K_M size
- 5.3 GB
- Q8_0 size
- 9.3 GB
- Context
- 128k
- Ollama tag
- granite4.1:8b
- Memory
- 16 GB unified
- Usable for weights
- ~12 GB
- Power draw
- ~14 W
- Best runtime
- MLX (via Python or Swift; mlx-lm package)
You could also run
Run Granite 4.1 8B on other hardware
FAQ
Can iPad Pro M4 (16GB, 1TB/2TB config) run Granite 4.1 8B?
Yes. Granite 4.1 8B runs on iPad Pro M4 (16GB, 1TB/2TB config) at Q4_K_M (~6.8 GB of ~12 GB usable).
How much memory does Granite 4.1 8B need?
iPad Pro M4 (16GB, 1TB/2TB config) has room to spare. At Q4_K_M the weights are ~5.3 GB; with KV cache and runtime overhead, budget ~6.8 GB at a 4k context.
What is the best tool to run Granite 4.1 8B on iOS?
On iPhone and iPad, Apple Foundation Models (Built into iOS 26, ~3B on-device model, zero download, fully private.) is the standard choice. Phones realistically run 1B-4B class models. Anything larger thermally throttles or OOMs.
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Weights are measured from GGUF files; KV cache and overhead are computed, so totals can vary ~15% with context and runtime. Any tok/s is a bandwidth estimate. See methodology.